Biblio

The analysis shows how important Power Network Measuring and Characterization (PSMC) is to the plan. Networks planning and oversight for the transmission of electrical energy is becoming increasingly frequent. In reaction to the current contest of assimilating trying to cut charging in the crate, estimation, information sharing, but rather govern into PSMC reasonable quantities, Electrical Transmit Monitoring and Management provides a thorough outline of founding principles together with smart sensors for domestic spying, security precautions, and control of developed broadening power systems.Electricity supply control must depend increasingly heavily on telecommunications infrastructure to manage and run their processes because of the fluctuation in transmission and distribution of electricity. A wider attack surface will also be available to threat hackers as a result of the more communications. Large-scale blackout have occurred in the past as a consequence of cyberattacks on electrical networks. In order to pinpoint the key issues influencing power grid computer networks, we looked at the network infrastructure supporting electricity grids in this research.

The agricultural sector and other Micro, Small, and Medium Enterprises in India operate with more than 90% migrant workers searching for better employment opportunities far away from their native places. However, inherent challenges are far more for the migrant workers, most prominently their Identity. To the best of our knowledge, available literature lacks a comprehensive study on identity management components for user privacy and data protection mechanisms in identity management architecture. Self-Sovereign Identity is regarded as a new evolution in digital identity management systems. Blockchain technology and distributed ledgers bring us closer to realizing an ideal Self-Sovereign Identity system. This paper proposes a novel solution to address identity issues being faced by migrant workers. It also gives a holistic, coherent, and mutually beneficial Identity Management Solution for the migrant workforce in the Indian perspective towards e-Governance and Digital India.

Cloud computing plays major role in the development of accessing clouduser’s document and sensitive information stored. It has variety of content and representation. Cyber security and attacks in the cloud is a challenging aspect. Information security attains a vital part in Cyber Security management. It involves actions intended to reduce the adverse impacts of such incidents. To access the documents stored in cloud safely and securely, access control will be introduced based on cloud users to access the user’s document in the cloud. To achieve this, it is highly required to combine security components (e.g., Access Control, Usage Control) in the security document to get automatic information. This research work has proposed a Role Key Homomorphic Encryption Algorithm (RKHEA) to monitor the cloud users, who access the services continuously. This method provides access creation of session-based key to store the singularized encryption to reduce the key size from random methods to occupy memory space. It has some terms and conditions to be followed by the cloud users and also has encryption method to secure the document content. Hence the documents are encrypted with the RKHEA algorithm based on Service Key Access (SKA). Then, the encrypted key will be created based on access control conditions. The proposed analytics result shows an enhanced control over the documents in cloud and improved security performance.

Transmitting data through the internet may have severe security risks due to illegal access done by attackers. Some methods have been introduced to overcome this issue, such as cryptography and steganography. Nevertheless, some problems still arise, such as the quality of the stego data. Specifically, it happens if the stego is shared with some users. In this research, a shared-secret mechanism is combined with steganography. For this purpose, the fuzzy logic edge detection and Prediction Error (PE) methods are utilized to hide private data. The secret sharing process is carried out after data embedding in the cover image. This sharing mechanism is performed on image pixels that have been converted to PE values. Various Peak Signal to Noise Ratio (PSNR) values are obtained from the experiment. It is found that the number of participants and the threshold do not significantly affect the image quality of the shares.

Data Protection and Consenting Communication Mechanisms (DPCCMs) enable users to express their privacy decisions and manage their online consent. Thus, they can become a crucial means of protecting individuals' online privacy and agency, thereby replacing the current problematic practices such as “consent dialogues”. Based on an in-depth analysis of different DPCCMs, we propose an interdisciplinary set of factors that can be used for a comparison of such mechanisms. Moreover, we use the results from a qualitative expert study to identify some of the main multidisciplinary challenges that DPCCMs should address to become widely adopted data privacy mechanisms. We leverage both the factors and the challenges to compare two current open specifications, i.e. the Advanced Data Protection Control (ADPC) and the Global Privacy Control (GPC), and discuss future work.

With the advent of ease of access to the internet and an increase in digital literacy among citizens, digitization of the banking sector has throttled. Countries are now aiming for a cashless society. The introduction of a Unified Payment Interface (UPI) by the National Payments Corporation of India (NPCI) in April 2016 is a game-changer for cashless models. UPI payment model is currently considered the world’s most advanced payment system, and we see many countries adopting this cashless payment mode. With the increase in its popularity, there arises the increased need to strengthen the security posture of the payment solution. In this work, we explore the privacy challenges in the existing data flow of UPI models and propose approaches to preserve the privacy of customers using the Unified Payments Interface.

Data security is the process of protecting data from loss, alteration, or unauthorised access during its entire lifecycle. It includes everything from the policies and practices of a company to the hardware, software, storage, and user devices used by that company. Data security tools and technology increase transparency into an organization's data and its usage. These tools can protect data by employing methods including encryption and data masking personally identifiable information.. Additionally, the method aids businesses in streamlining their auditing operations and adhering to the increasingly strict data protection rules.

The development of cloud apps enables people to exchange resources, goods, and expertise online with other clients. The material is more vulnerable to numerous security dangers from outsiders due to the fact that millions of users exchange data through the same system. How to maintain the security of this data is now the main concern. The current data protection system functions best when it places a greater priority on safeguarding data maintained in online storage than it does on cybersecurity during transportation. The data becomes open to intrusion attacks while being transferred. Additionally, the present craze states that an outside auditor may view data as it is being transmitted. Additionally, by allowing the hacker to assume a third-person identity while obtaining the information, this makes the data more susceptible to exploitation. The proposed system focuses on using encryption to safeguard information flow since cybersecurity is seen as a major issue. The approach also takes into account the fourth auditing issue, which is that under the recommended manner, the inspector is not allowed to see the user information. Tests have shown that the recommended technique improves security overall by making it harder for hackers to decode the supplied data.

There is a stark contrast between the state of cyber security of national infrastructure in Ireland and the efforts underway to support cyber security technologists to work in the country. Notable attacks have recently occurred against the national health service, universities, and various other state bodies, prompting an interest in changing the current situation. This paper presents an overview of the security projects, commercial establishments, and policy in Ireland.

Differential privacy is a widely-used metric, which provides rigorous privacy definitions and strong privacy guarantees. Much of the existing studies on differential privacy are based on datasets where the tuples are independent, and thus are not suitable for correlated data protection. In this paper, we focus on correlated differential privacy, by taking the data correlations and the prior knowledge of the initial data into account. The data correlations are modeled by Bayesian conditional probabilities, and the prior knowledge refers to the exact values of the data. We propose general correlated differential privacy conditions for the discrete and continuous random noise-adding mechanisms, respectively. In case that the conditions are inaccurate due to the insufficient prior knowledge, we introduce the tuple dependence based on rough set theory to improve the correlated differential privacy conditions. The obtained theoretical results reveal the relationship between the correlations and the privacy parameters. Moreover, the improved privacy condition helps strengthen the mechanism utility. Finally, evaluations are conducted over a micro-grid system to verify the privacy protection levels and utility guaranteed by correlated differential private mechanisms.

The digital transformation brought on by 5G is redefining current models of end-to-end (E2E) connectivity and service reliability to include security-by-design principles necessary to enable 5G to achieve its promise. 5G trustworthiness highlights the importance of embedding security capabilities from the very beginning while the 5G architecture is being defined and standardized. Security requirements need to overlay and permeate through the different layers of 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture within a risk-management framework that takes into account the evolving security-threats landscape. 5G presents a typical use-case of wireless communication and computer networking convergence, where 5G fundamental building blocks include components such as Software Defined Networks (SDN), Network Functions Virtualization (NFV) and the edge cloud. This convergence extends many of the security challenges and opportunities applicable to SDN/NFV and cloud to 5G networks. Thus, 5G security needs to consider additional security requirements (compared to previous generations) such as SDN controller security, hypervisor security, orchestrator security, cloud security, edge security, etc. At the same time, 5G networks offer security improvement opportunities that should be considered. Here, 5G architectural flexibility, programmability and complexity can be harnessed to improve resilience and reliability. The working group scope fundamentally addresses the following: •5G security considerations need to overlay and permeate through the different layers of the 5G systems (physical, network, and application) as well as different parts of an E2E 5G architecture including a risk management framework that takes into account the evolving security threats landscape. •5G exemplifies a use-case of heterogeneous access and computer networking convergence, which extends a unique set of security challenges and opportunities (e.g., related to SDN/NFV and edge cloud, etc.) to 5G networks. Similarly, 5G networks by design offer potential security benefits and opportunities through harnessing the architecture flexibility, programmability and complexity to improve its resilience and reliability. •The IEEE FNI security WG's roadmap framework follows a taxonomic structure, differentiating the 5G functional pillars and corresponding cybersecurity risks. As part of cross collaboration, the security working group will also look into the security issues associated with other roadmap working groups within the IEEE Future Network Initiative.

The growth of ICTs and the resulting data explosion could pave the way for the surveillance of our lives and diminish our democratic freedoms, at an unimaginable scale. Consumer mistrust of an organization's ability to safeguard their data is at an all time high and this has negative implications for Big Data. The timing is right to be proactive about designing privacy into technologies, business processes and networked infrastructures. Inclusiveness of all objectives can be achieved through consultation, co-operation, and collaboration (3 C's). If privacy is the default, without diminishing functionality or other legitimate interests, then trust will be preserved and innovation will flourish.

Internet of Medical Things (IoMT) is a rapidly growing branch of IoT (Internet of Things), which requires special treatment to cyber security due to confidentiality of healthcare data and patient health threat. Healthcare data and automated medical devices might become vulnerable targets of malicious cyber-attacks. While a large number of robotic applications, including medical and healthcare, employ robot operating system (ROS) as their backbone, not enough attention is paid for ROS security. The paper discusses a security of ROS-based swing doors automation in the context of a robotic hospital framework, which should be protected from cyber-attacks.

The concept of a microgrid has emerged as a promising solution for the management of local groups of electricity consumers and producers. The use of end-users' energy usage data can help in increasing efficient operation of a microgrid. However, existing data-aggregation schemes for a microgrid suffer different cyber attacks and do not provide high level of accuracy. This work aims at designing a privacy-preserving data-aggregation scheme for a microgrid of prosumers that achieves high level of accuracy, thereby benefiting to the management and control of a microgrid. First, a novel smart meter readings data protection mechanism is proposed to ensure privacy of prosumers by hiding the real energy usage data from other parties. Secondly, a blockchain-based data-aggregation scheme is proposed to ensure privacy of the end-users, while achieving high level of accuracy in terms of the aggregated data. The proposed data-aggregation scheme is evaluated using real smart meter readings data from 100 prosumers. The results show that the proposed scheme ensures prosumers' privacy and achieves high level of accuracy, while it is secure against eavesdropping and man-in-the-middle cyber attacks.

In the context of cybersecurity systems, trust is the firm belief that a system will behave as expected. Trustworthiness is the proven property of a system that is worthy of trust. Therefore, trust is ephemeral, i.e. trust can be broken; trustworthiness is perpetual, i.e. trustworthiness is verified and cannot be broken. The gap between these two concepts is one which is, alarmingly, often overlooked. In fact, the pressure to meet with the pace of operations for mission critical cross domain solution (CDS) development has resulted in a status quo of high-risk, ad hoc solutions. Trustworthiness, proven through formal verification, should be an essential property in any hardware and/or software security system. We have shown, in "vCDS: A Virtualized Cross Domain Solution Architecture", that developing a formally verified CDS is possible. virtual CDS (vCDS) additionally comes with security guarantees, i.e. confidentiality, integrity, and availability, through the use of a formally verified trusted computing base (TCB). In order for a system, defined by an architecture description language (ADL), to be considered trustworthy, the implemented security configuration, i.e. access control and data protection models, must be verified correct. In this paper we present the first and only security auditing tool which seeks to verify the security configuration of a CDS architecture defined through ADL description. This tool is useful in mitigating the risk of existing solutions by ensuring proper security enforcement. Furthermore, when coupled with the agile nature of vCDS, this tool significantly increases the pace of system delivery.

This paper proposes a cybersecurity maturity model to assess the capabilities of medical organizations to identify their level of maturity, prioritizing privacy and personal data protection. There are problems such as data breaches, the lack of security measures in health information, and the poor capacity of organizations to handle cybersecurity threats that generate concern in the health sector as they seek to mitigate risks in cyberspace. The proposal, based upon C2M2 (Cybersecurity Capability Maturity Model), incorporates practices and controls which allow organizations to identify security gaps generated through cyberattacks on sensitive health patient data. This model seeks to integrate the best practices related to privacy and protection of personal data in the Peruvian legal framework through the Administrative Directive No. 294-MINSA and the personal data protection Act No. 29733. The model consists of 3 evaluation phases. 1. Assessment planning; 2. Execution of the evaluation; 3. Implementation of improvements. The model was validated and tested in a public sector medical organization in Lima, Peru. The preliminary results showed that the organization is at Level 1 with 14% of compliance with established controls, 34% in risk, threat and vulnerability management practices and 19% in supply chain management. These the 3 highest percentages of the 10 evaluated domains.

Decentralized Identifiers (DIDs) and Self-Sovereign Identity (SSI) are emerging decentralized identity solutions. DIDs allow legal entities like organizations to create and fully control their identifiers while building the necessary infrastructure for SSI, enabling entities like persons, organizations, or machines to fully control and own their digital identities without the involvement of an intermediate central authority. DIDs are identifiers that are used to reference entities unambiguously and, together with DID Documents stored in a verifiable data registry, establish a new, decentralized public-key infrastructure. An SSI-based digital identity may be composed of many different claims certified by an issuer. Examples are the identity holder’s name, age, gender, university degree, driving license, or other attributes. What makes SSI unique compared to other identity management solutions is that the users keep their digital identities in storage of their choice and thus determine their distribution and processing.With this privacy-by-design approach, the emergence of DIDs and SSI can shape the architecture of the future Internet and its applications, which will impact the future of mobile networks. While 5G networks are currently being rolled out, a discussion about the new capabilities of 6G networks, which are still in the distant future, has long since begun. In addition to even faster access, shorter delays, and new applications, features such as human-centricity, data protection, and privacy are being addressed in particular in the discussions. These latter points make DIDs, SSI, and related concepts and architectures promising candidates for 6G adoption.The talk gives a brief introduction to DIDs and SSI and then discusses the benefits and drawbacks the integration of these technologies into 6G may have. Furthermore, the talk identifies different use cases and identifies the system components and functions of cellular networks affected by a 6G integration.

The presence of experts, such as a data protection officer (DPO) and a privacy engineer is essential in Privacy Requirements Engineering. This task is carried out in various forms including threat modeling and privacy impact assessment. The knowledge required for performing privacy threat modeling can be a serious challenge for a novice privacy engineer. We aim to bridge this gap by developing an automated approach via machine learning that is able to detect privacy-related entities in the user stories. The relevant entities include (1) the Data Subject, (2) the Processing, and (3) the Personal Data entities. We use a state-of-the-art Named Entity Recognition (NER) model along with contextual embedding techniques. We argue that an automated approach can assist agile teams in performing privacy requirements engineering techniques such as threat modeling, which requires a holistic understanding of how personally identifiable information is used in a system. In comparison to other domain-specific NER models, our approach achieves a reasonably good performance in terms of precision and recall.

This article discusses the problem of information security management in computer systems and describes the process of developing an algorithm that allows to determine measures to protect personal data. The organizational and technical measures formulated by the FSTEC are used as measures.

In this work an overview of basic approaches to choosing protective measures for automated process control systems is done. The aim of the research was to develop a method for choosing protection measures for information security at every APCs level using set theory within analysis of basic sets of protection measures. In the framework of the research relevant attacks on industrial infrastructure are considered, an algorithm of choosing APCs protective measures is constructed, and it is suggested that it is required to use protective measures for every system level in accordance with an individual assessment of data protection class at the corresponding level. The authors concluded that it is necessary to exclude from consideration “specification of an adapted basic set” of the algorithm for choosing APCs protection measures in case the adapted basic set of APCs protective measures provides blocking all security threats at the considered system level. The approach to choosing protection measures based on building Euler-Venn diagrams is suggested. The results of the research are recommended to be used when modeling information security threats and developing requirements for APCs information protection means.

Physical-layer security is a new paradigm that offers data protection against eavesdropping in wireless 5G networks. In this context, the Gaussian channel is a typical model that captures the practical aspects of confidentially transmitting a message through the wireless medium. In this paper, we consider the peculiar case of transmitting a message through a wireless, state-dependent channel which is prone to eavesdropping, where the state knowledge is non-causally known and shared between the sender and the eavesdropper. We show that a novel structured coding scheme, which combines random coding arguments and the dirty-paper coding technique, achieves the fundamental limit of secure and reliable communication for the considered model.

Data and veracious information are an important feature of any organization; it takes special care as a like asset of the organization. Cloud computing system main target to provide service to the user like high-speed access user data for storage and retrieval. Now, big concern is data protection in cloud computing technology as because data leaking and various malicious attacks happened in cloud computing technology. This study provides user data protection in the cloud storage device. The article presents the architecture of a data security hybrid infrastructure that protects and stores the user data from the unauthenticated user. In this hybrid model, we use a different type of security model.

Cloud computing has changed how humans use their technological expertise. It indicates a transition in the use of computers as utilitarian instruments with radical applications in general. However, as technology advances, the number of hazards increases and crucial data protection has become increasingly challenging due to extensive internet use. Every day, new encryption methods are developed, and much research is carried out in the search for a reliable cryptographic algorithm. The AES algorithm employs an overly simplistic algebraic structure. Each block employs the same encryption scheme, and AES is subject to brute force and MITM attacks. AES have not provide d sufficient levels of security; the re is still a need to put further le vels of protection over them. In this regard, DNA cryptography allows you to encrypt a large quantity of data using only a few amount of DNA. This paper combines two methodologies, a DNA-based algorithm and the AES Algorithm, to provide a consi derably more secure data security platform. The DNA cryptography technology and the AES approach are utilized for data encryption and decryption. To improve cloud security, DNA cryptography and AES provide a technologically ideal option.

Nowadays a huge amount of sensitive information is sending via packet data networks and its security doesn't provided properly. Very often information leakage causes huge damage to organizations. One of the mechanisms to cause information leakage when it transmits through a communication channel is to construct a covert channel. Everywhere used packet networks provide huge opportunities for covert channels creating, which often leads to leakage of critical data. Moreover, covert channels based on packet length modifying can function in a system even if traffic encryption is applied and there are some data transfer schemes that are difficult to detect. The purpose of the paper is to construct and examine a normalization protection tool against covert channels. We analyze full and partial normalization, propose estimation of the residual covert channel capacity in a case of counteracting and determine the best parameters of counteraction tool.

Being compliant with the GDPR (and data protection regulations in general) is a difficult task, that calls for manifold, computer-based automated support. In this context, several use cases related to the management and the enforcement of privacy policies and consent call for a machine-understandable policy language, equipped with reliable algorithms for compliance checking and explanations. In this paper, we outline a set of requirements for such languages and algorithms, and address such requirements with a framework based on a profile of OWL2 and a set of policy serializations based on popular formats such as ODRL and JSON. Such ``external'' policy syntax is translated into the ``internal'' OWL2 syntax, thereby enabling semantic compliance checking and explanations using specialized OWL2 reasoners. We provide a precise definition of both the OWL2 profile and the external policy language based on JSON.